0-1测试法是通过离散数据转化变量的线性增长率K(c)的输出值是否趋近于1或0来判断离散序列是否具有混沌特性的新方法.以经典Verhulst种群模型生成的3组时间序列（弱混沌、完全混沌、3-周期）为研究对象，对不同的增长因子SymbollAp和数据长度N进行序列模拟，验证0-1测试方法的有效性和抗噪性.结果显示：0-1测试法能有效识别Verhulst序列的混沌特征，其中弱混沌序列K(c)值随数据长度的增加不断增大到0-700，完全混沌序列的K(c)值趋于1，3-周期序列K(c)值趋于0；进一步对3种序列添加正态白噪声（噪声比=5%），添加后对应K(c)值的变化不大，说明低强度噪声并不能影响其序列具有的内在非线性特性， 即0-1测试法具有一定的抗噪性.
Abstract
The 0-1 test method is a new method which the chaos of discrete time series can be determined by the condition that the discrete data transformation variable's linear growth rate K(c) approaches to 1 or 0. Three groups of time series (weak chaos, strong chaos and 3 period-doubling) are generated by classic Verhulst population model as the research object is to simulate different values of growth factor (SymbollAp) and data length N, and test the efficiency anti-noise capacity of this method. The result shows that the 0-1 test method can effectively identify the chaos characteristics of the Verhulst series, the K(c) value of weak chaos series increases to 0.700 3 as the data length increased, and the K(c)value is approximate to 1 for strong chaos series and 3 period-doubling seriesK(c)is close to 0. After adding white Gaussian noise (noise ratio=5%) to three time series, the corresponding K(c)value does not change greatly. This suggests that the low intensity noise does not affect its intrinsic nonlinear characteristics, and the 0-1 method has a certain resistance to noise.
关键词
0-1测试 /
混沌识别 /
Verhulst种群模型 /
正态白噪声
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Key words
0-1 test /
chaos identification /
Verhulst population model /
normal white noise
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脚注
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基金
国家自然科学基金资助项目(41172295)
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